Abstract Machine learning has opened the door for the automated sorting (classification) of images, holograms and acoustic backscatters of individual plankton, invertebrates, fish and marine mammals. However, this field is complicated by decades of paradoxically promising reports of classifier performance that do not correlate with real‐world uptake of
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Area efficient approximate multiplier based on novel 4:2 compressors and error correction logic. [PDF]
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Robust missing data reconstruction in schizophrenia using tracking-removed autoencoder with fuzzy confidence integration. [PDF]
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